Seismic data is collected to analyze the subsurface of the Earth, and is particularly collected in connection with hydrocarbon exploration and production activities. Seismic data for analyzing subsurface structures may be collected on land or over water. In order to obtain seismic data, an acoustic source is used which typically consists of explosives or a seismic vibrator on land or an impulse of compressed air at sea. The seismic signals reflected by the various geologic layers beneath the surface of the Earth are known as traces and are sensed by a large number, typically hundreds or thousands, of sensors such as geophones on land and hydrophones at sea. The reflected signals are recorded and the results are analyzed to derive an indication of the geology in the subsurface. Such indications may then be used to assess the likelihood and location of potential hydrocarbon deposits.
Seismic surveys are generally conducted using one or more receiver lines having a plurality of receiver station locations spaced evenly along their lengths. In a two dimensional (2D) survey, a single receiver line is used and the acoustic source is typically positioned at various points in-line with the receiver line. In a three dimensional survey, a plurality of parallel receiver lines are typically used and the acoustic source is generally positioned at various points offset from the receiver lines. While a 2D seismic survey can only create a cross-sectional representation of the subsurface, a 3D seismic survey can be used to develop a three dimensional representation of the subsurface.
The desired reflection signals can be masked by noise. Seismic data are subject to a wide variety of noise related problems that can and do limit its usefulness. Broadly speaking, noise found in seismic traces is either incoherent or coherent. Incoherent ambient noise, or uncorrelated “white” noise, is ubiquitous and is generally greatly attenuated through the simple expedient of stacking, although extremely large individual data values (“spikes”) and “bad” traces often need special attention. Coherent, or correlated, noise on the other hand cannot usually be so readily eliminated. Some common examples of coherent noise (some of which affect land surveys more than surveys) include multiple reflections, ground roll generated by the seismic source vibrations, air waves, guided waves, sideswipe, cable noise and 60 hertz power line noise.
In conventional seismic data acquisition systems, data are inherently filtered through use of “hard-wired” (electrically connected) groups of sensors. A group or receiver array delivers a single output trace (the normalized sum or arithmetic average of the output of all individual sensors of the group) at the particular receiver station location about which the sensors are placed. The single trace is the normalized sum or arithmetic average of the output of all individual sensors making up the group.
More recently, however, seismic surveys have been performed using receiver systems referred to as “single sensor” or “point receiver” in which the digital outputs of multiple sensors are [recorded and] processed individually. The inherent filtering effect of the hard-wired group is then replaced by signal filters that are better adapted to the nature of seismic noise and preserve more of the seismic reflection signals. Transition to point receiver arrays for land seismic has been described in “New Directions in land Seismic Technology” in Oilfield Review, Autumn 2005 pages 42-53.
U.S. Pat. Nos. 6,446,008 and 7,584,057 both disclose filtering of signals to remove noise. The latter document discloses use of a mathematical technique, Alternating Projections onto Convex Sets (APOCS), to design multi-dimensional digital filters for land seismic.
Filters for signals are classified as either infinite impulse response (IIR) filters which theoretically produce an output for an indefinite period after receiving an input signal and finite impulse response (FIR) filters which return to zero output within a finite period (or at once) when input ceases. Filters are also classified as adaptive, if the filter coefficients change in response to the signal data encountered (which may be recorded signal data) or as fixed or non-adaptive if the filter coefficients or the manner in which they are calculated is predetermined without detailed knowledge of the signal data.
A filter for digital signals can be implemented in software as computational processing of the signal data (which may be recorded signal data). The filter applies coefficients to alter the amplitude of the signal data and in doing so attenuates parts of that data relative to other parts, with the objective of attenuating the parts which are unwanted noise. Design of such a filter entails computation of the coefficients. The characteristics of a filter are generally referred to as its response.
It is an object of the present invention to provide methods for processing seismic data, particularly methods for designing and applying filters for such data.